Overview

Dataset statistics

Number of variables17
Number of observations141362
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.5 MiB
Average record size in memory115.0 B

Variable types

Numeric14
Boolean3

Alerts

studio has constant value "False"Constant
build_year is highly overall correlated with floors_totalHigh correlation
building_type_int is highly overall correlated with ceiling_heightHigh correlation
ceiling_height is highly overall correlated with building_type_intHigh correlation
floor is highly overall correlated with floors_totalHigh correlation
floors_total is highly overall correlated with build_year and 1 other fieldsHigh correlation
living_area is highly overall correlated with rooms and 1 other fieldsHigh correlation
price is highly overall correlated with rooms and 1 other fieldsHigh correlation
rooms is highly overall correlated with living_area and 2 other fieldsHigh correlation
total_area is highly overall correlated with living_area and 2 other fieldsHigh correlation
has_elevator is highly imbalanced (52.3%)Imbalance
is_apartment is highly imbalanced (92.1%)Imbalance
price is highly skewed (γ1 = 88.96515049)Skewed
id is uniformly distributedUniform
id has unique valuesUnique
building_type_int has 1927 (1.4%) zerosZeros
kitchen_area has 11701 (8.3%) zerosZeros
living_area has 18588 (13.1%) zerosZeros

Reproduction

Analysis started2024-07-10 07:23:31.928132
Analysis finished2024-07-10 07:24:16.653130
Duration44.72 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

id
Real number (ℝ)

UNIFORM  UNIQUE 

Distinct141362
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70681.5
Minimum1
Maximum141362
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:16.770410image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7069.05
Q135341.25
median70681.5
Q3106021.75
95-th percentile134293.95
Maximum141362
Range141361
Interquartile range (IQR)70680.5

Descriptive statistics

Standard deviation40807.839
Coefficient of variation (CV)0.57734823
Kurtosis-1.2
Mean70681.5
Median Absolute Deviation (MAD)35340.5
Skewness0
Sum9.9916782 × 109
Variance1.6652797 × 109
MonotonicityStrictly increasing
2024-07-10T07:24:17.020905image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
141362 1
 
< 0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
Other values (141352) 141352
> 99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
141362 1
< 0.1%
141361 1
< 0.1%
141360 1
< 0.1%
141359 1
< 0.1%
141358 1
< 0.1%
141357 1
< 0.1%
141356 1
< 0.1%
141355 1
< 0.1%
141354 1
< 0.1%
141353 1
< 0.1%

build_year
Real number (ℝ)

HIGH CORRELATION 

Distinct118
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1986.6
Minimum1901
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:17.269220image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1901
5-th percentile1957
Q11969
median1985
Q32007
95-th percentile2017
Maximum2023
Range122
Interquartile range (IQR)38

Descriptive statistics

Standard deviation22.136409
Coefficient of variation (CV)0.011142861
Kurtosis-0.1394151
Mean1986.6
Median Absolute Deviation (MAD)18
Skewness-0.38696514
Sum2.8082976 × 108
Variance490.02061
MonotonicityNot monotonic
2024-07-10T07:24:17.516759image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2017 4461
 
3.2%
2018 4386
 
3.1%
1968 3502
 
2.5%
2015 3466
 
2.5%
1969 3322
 
2.3%
1972 3256
 
2.3%
1970 3210
 
2.3%
1971 3197
 
2.3%
1967 3191
 
2.3%
2006 2874
 
2.0%
Other values (108) 106497
75.3%
ValueCountFrequency (%)
1901 10
 
< 0.1%
1902 75
0.1%
1903 28
 
< 0.1%
1904 32
 
< 0.1%
1905 74
0.1%
1906 33
 
< 0.1%
1907 42
 
< 0.1%
1908 27
 
< 0.1%
1909 11
 
< 0.1%
1910 130
0.1%
ValueCountFrequency (%)
2023 3
 
< 0.1%
2022 236
 
0.2%
2021 131
 
0.1%
2020 587
 
0.4%
2019 1257
 
0.9%
2018 4386
3.1%
2017 4461
3.2%
2016 2540
1.8%
2015 3466
2.5%
2014 2680
1.9%

building_type_int
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.232941
Minimum0
Maximum6
Zeros1927
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:17.705183image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q34
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4594606
Coefficient of variation (CV)0.45143434
Kurtosis-0.67749025
Mean3.232941
Median Absolute Deviation (MAD)0
Skewness-0.25416628
Sum457015
Variance2.1300252
MonotonicityNot monotonic
2024-07-10T07:24:17.871134image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
4 78696
55.7%
2 25265
 
17.9%
1 23164
 
16.4%
6 10533
 
7.5%
0 1927
 
1.4%
3 1773
 
1.3%
5 4
 
< 0.1%
ValueCountFrequency (%)
0 1927
 
1.4%
1 23164
 
16.4%
2 25265
 
17.9%
3 1773
 
1.3%
4 78696
55.7%
5 4
 
< 0.1%
6 10533
 
7.5%
ValueCountFrequency (%)
6 10533
 
7.5%
5 4
 
< 0.1%
4 78696
55.7%
3 1773
 
1.3%
2 25265
 
17.9%
1 23164
 
16.4%
0 1927
 
1.4%

latitude
Real number (ℝ)

Distinct15720
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.730059
Minimum55.21146
Maximum56.011032
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:18.081310image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum55.21146
5-th percentile55.567215
Q155.653858
median55.724686
Q355.807323
95-th percentile55.883572
Maximum56.011032
Range0.79957199
Interquartile range (IQR)0.15346527

Descriptive statistics

Standard deviation0.10261107
Coefficient of variation (CV)0.0018412159
Kurtosis-0.35001837
Mean55.730059
Median Absolute Deviation (MAD)0.076637268
Skewness-0.0075277291
Sum7878112.6
Variance0.010529032
MonotonicityNot monotonic
2024-07-10T07:24:18.335878image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55.77080536 565
 
0.4%
55.78516769 381
 
0.3%
55.83548737 285
 
0.2%
55.55776596 257
 
0.2%
55.74351883 251
 
0.2%
55.83442688 235
 
0.2%
55.77090073 220
 
0.2%
55.78421021 210
 
0.1%
55.69994354 192
 
0.1%
55.59153748 167
 
0.1%
Other values (15710) 138599
98.0%
ValueCountFrequency (%)
55.21146011 5
< 0.1%
55.21229935 3
 
< 0.1%
55.21334457 2
 
< 0.1%
55.21493912 10
< 0.1%
55.21569824 3
 
< 0.1%
55.30972672 3
 
< 0.1%
55.31040192 2
 
< 0.1%
55.3139801 1
 
< 0.1%
55.31425476 2
 
< 0.1%
55.31481552 1
 
< 0.1%
ValueCountFrequency (%)
56.0110321 14
< 0.1%
56.00934601 18
< 0.1%
56.00914001 5
 
< 0.1%
56.00882339 2
 
< 0.1%
56.00848389 1
 
< 0.1%
56.00812149 4
 
< 0.1%
56.00805664 7
 
< 0.1%
56.00751877 4
 
< 0.1%
56.00745773 4
 
< 0.1%
56.00717163 2
 
< 0.1%

longitude
Real number (ℝ)

Distinct15271
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.589235
Minimum36.864372
Maximum37.946411
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:18.721416image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum36.864372
5-th percentile37.354996
Q137.491764
median37.581146
Q337.691055
95-th percentile37.828963
Maximum37.946411
Range1.0820389
Interquartile range (IQR)0.19929123

Descriptive statistics

Standard deviation0.15012178
Coefficient of variation (CV)0.0039937439
Kurtosis0.31447965
Mean37.589235
Median Absolute Deviation (MAD)0.094726562
Skewness-0.1160192
Sum5313689.4
Variance0.022536548
MonotonicityNot monotonic
2024-07-10T07:24:18.980463image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5642128 581
 
0.4%
37.56404114 407
 
0.3%
37.65834808 316
 
0.2%
37.55502319 257
 
0.2%
37.42210007 251
 
0.2%
37.65960312 246
 
0.2%
37.56266785 227
 
0.2%
37.37809753 220
 
0.2%
37.63718414 188
 
0.1%
37.45571518 168
 
0.1%
Other values (15261) 138501
98.0%
ValueCountFrequency (%)
36.86437225 13
< 0.1%
36.86503601 20
< 0.1%
36.86519623 3
 
< 0.1%
36.86552811 3
 
< 0.1%
36.86582565 16
< 0.1%
36.86593246 1
 
< 0.1%
36.8693924 5
 
< 0.1%
36.87020111 4
 
< 0.1%
36.87042618 2
 
< 0.1%
36.87133408 2
 
< 0.1%
ValueCountFrequency (%)
37.94641113 27
 
< 0.1%
37.94482803 19
 
< 0.1%
37.9413147 43
< 0.1%
37.94092178 27
 
< 0.1%
37.94085693 105
0.1%
37.94051743 7
 
< 0.1%
37.94021988 10
 
< 0.1%
37.93956375 82
0.1%
37.93946457 26
 
< 0.1%
37.9389267 15
 
< 0.1%

ceiling_height
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7536498
Minimum2
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:19.206176image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.48
Q12.6400001
median2.6400001
Q32.8
95-th percentile3.0999999
Maximum27
Range25
Interquartile range (IQR)0.15999985

Descriptive statistics

Standard deviation0.22327539
Coefficient of variation (CV)0.081083437
Kurtosis1009.3248
Mean2.7536498
Median Absolute Deviation (MAD)0.059999943
Skewness11.564608
Sum389261.44
Variance0.049851898
MonotonicityNot monotonic
2024-07-10T07:24:19.438328image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.640000105 58512
41.4%
3 22933
 
16.2%
2.700000048 14993
 
10.6%
2.480000019 7904
 
5.6%
2.799999952 7425
 
5.3%
2.74000001 6724
 
4.8%
3.200000048 3819
 
2.7%
2.5 3813
 
2.7%
3.099999905 2906
 
2.1%
2.75 2118
 
1.5%
Other values (67) 10215
 
7.2%
ValueCountFrequency (%)
2 12
 
< 0.1%
2.25 1
 
< 0.1%
2.299999952 5
 
< 0.1%
2.400000095 31
 
< 0.1%
2.450000048 17
 
< 0.1%
2.480000019 7904
5.6%
2.5 3813
2.7%
2.50999999 2
 
< 0.1%
2.529999971 9
 
< 0.1%
2.539999962 104
 
0.1%
ValueCountFrequency (%)
27 1
 
< 0.1%
8 6
 
< 0.1%
7 4
 
< 0.1%
6 17
 
< 0.1%
5.199999809 1
 
< 0.1%
5 6
 
< 0.1%
4.599999905 4
 
< 0.1%
4.5 14
 
< 0.1%
4.190000057 40
< 0.1%
4.150000095 47
< 0.1%

flats_count
Real number (ℝ)

Distinct706
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean251.99323
Minimum1
Maximum4455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:19.675287image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile58
Q1111
median200
Q3324
95-th percentile624
Maximum4455
Range4454
Interquartile range (IQR)213

Descriptive statistics

Standard deviation207.33617
Coefficient of variation (CV)0.82278468
Kurtosis12.928546
Mean251.99323
Median Absolute Deviation (MAD)100
Skewness2.702838
Sum35622267
Variance42988.287
MonotonicityNot monotonic
2024-07-10T07:24:19.908602image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 4189
 
3.0%
144 2820
 
2.0%
84 2638
 
1.9%
72 2335
 
1.7%
215 2281
 
1.6%
287 2179
 
1.5%
60 1967
 
1.4%
192 1791
 
1.3%
98 1663
 
1.2%
143 1600
 
1.1%
Other values (696) 117899
83.4%
ValueCountFrequency (%)
1 199
0.1%
2 71
 
0.1%
3 20
 
< 0.1%
4 27
 
< 0.1%
5 47
 
< 0.1%
6 40
 
< 0.1%
7 19
 
< 0.1%
8 62
 
< 0.1%
9 41
 
< 0.1%
10 151
0.1%
ValueCountFrequency (%)
4455 1
 
< 0.1%
1630 565
0.4%
1623 257
0.2%
1586 5
 
< 0.1%
1198 116
 
0.1%
1189 11
 
< 0.1%
1183 34
 
< 0.1%
1149 19
 
< 0.1%
1133 58
 
< 0.1%
1114 84
 
0.1%

floors_total
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.107554
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:20.133247image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q19
median14
Q317
95-th percentile25
Maximum99
Range98
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.8980454
Coefficient of variation (CV)0.48896113
Kurtosis5.5000767
Mean14.107554
Median Absolute Deviation (MAD)5
Skewness1.5626381
Sum1994272
Variance47.58303
MonotonicityNot monotonic
2024-07-10T07:24:20.371005image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 25042
17.7%
17 23221
16.4%
12 17177
12.2%
5 12702
9.0%
14 11566
8.2%
16 10260
7.3%
22 6147
 
4.3%
25 4476
 
3.2%
8 4005
 
2.8%
24 2631
 
1.9%
Other values (54) 24135
17.1%
ValueCountFrequency (%)
1 11
 
< 0.1%
2 54
 
< 0.1%
3 485
 
0.3%
4 930
 
0.7%
5 12702
9.0%
6 1727
 
1.2%
7 2062
 
1.5%
8 4005
 
2.8%
9 25042
17.7%
10 2502
 
1.8%
ValueCountFrequency (%)
99 1
 
< 0.1%
81 1
 
< 0.1%
70 1
 
< 0.1%
66 1
 
< 0.1%
60 1
 
< 0.1%
59 4
 
< 0.1%
58 77
0.1%
57 39
 
< 0.1%
56 184
0.1%
55 1
 
< 0.1%

has_elevator
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size138.2 KiB
True
126856 
False
14506 
ValueCountFrequency (%)
True 126856
89.7%
False 14506
 
10.3%
2024-07-10T07:24:20.615174image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

floor
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4673462
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:20.802330image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q310
95-th percentile18
Maximum56
Range55
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.7171437
Coefficient of variation (CV)0.76561921
Kurtosis5.2689924
Mean7.4673462
Median Absolute Deviation (MAD)3
Skewness1.6832674
Sum1055599
Variance32.685732
MonotonicityNot monotonic
2024-07-10T07:24:21.029706image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 14701
10.4%
3 13668
 
9.7%
5 12700
 
9.0%
4 12510
 
8.8%
1 11435
 
8.1%
6 9609
 
6.8%
7 9319
 
6.6%
8 8772
 
6.2%
9 8492
 
6.0%
10 5645
 
4.0%
Other values (46) 34511
24.4%
ValueCountFrequency (%)
1 11435
8.1%
2 14701
10.4%
3 13668
9.7%
4 12510
8.8%
5 12700
9.0%
6 9609
6.8%
7 9319
6.6%
8 8772
6.2%
9 8492
6.0%
10 5645
 
4.0%
ValueCountFrequency (%)
56 6
< 0.1%
55 6
< 0.1%
54 2
 
< 0.1%
53 11
< 0.1%
52 8
< 0.1%
51 10
< 0.1%
50 4
 
< 0.1%
49 7
< 0.1%
48 8
< 0.1%
47 3
 
< 0.1%

kitchen_area
Real number (ℝ)

ZEROS 

Distinct1036
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.001579
Minimum0
Maximum203
Zeros11701
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:21.263687image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.0999999
median8.8000002
Q310.2
95-th percentile17.299999
Maximum203
Range203
Interquartile range (IQR)4.0999999

Descriptive statistics

Standard deviation5.2640755
Coefficient of variation (CV)0.58479468
Kurtosis31.917312
Mean9.001579
Median Absolute Deviation (MAD)2.1999998
Skewness2.8364444
Sum1272481.2
Variance27.710491
MonotonicityNot monotonic
2024-07-10T07:24:21.516469image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 15584
 
11.0%
10 13323
 
9.4%
0 11701
 
8.3%
9 9594
 
6.8%
8 7550
 
5.3%
7 5654
 
4.0%
12 4591
 
3.2%
11 3566
 
2.5%
8.5 3225
 
2.3%
15 2301
 
1.6%
Other values (1026) 64273
45.5%
ValueCountFrequency (%)
0 11701
8.3%
1.5 1
 
< 0.1%
1.700000048 2
 
< 0.1%
1.799999952 1
 
< 0.1%
2 41
 
< 0.1%
2.099999905 1
 
< 0.1%
2.25 3
 
< 0.1%
2.299999952 2
 
< 0.1%
2.400000095 3
 
< 0.1%
2.5 8
 
< 0.1%
ValueCountFrequency (%)
203 1
 
< 0.1%
102 1
 
< 0.1%
100 3
< 0.1%
90 1
 
< 0.1%
87 1
 
< 0.1%
85 1
 
< 0.1%
83.40000153 1
 
< 0.1%
81 1
 
< 0.1%
80 6
< 0.1%
78 1
 
< 0.1%

living_area
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2345
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.056948
Minimum0
Maximum700
Zeros18588
Zeros (%)13.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:21.755710image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119
median29.4
Q341.400002
95-th percentile67
Maximum700
Range700
Interquartile range (IQR)22.400002

Descriptive statistics

Standard deviation23.96864
Coefficient of variation (CV)0.77176416
Kurtosis29.084183
Mean31.056948
Median Absolute Deviation (MAD)10.5
Skewness3.2220584
Sum4390272.3
Variance574.49569
MonotonicityNot monotonic
2024-07-10T07:24:21.987047image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18588
 
13.1%
19 5974
 
4.2%
20 4899
 
3.5%
30 3820
 
2.7%
18 3622
 
2.6%
32 3007
 
2.1%
28 2318
 
1.6%
31 2165
 
1.5%
45 2147
 
1.5%
34 1996
 
1.4%
Other values (2335) 92826
65.7%
ValueCountFrequency (%)
0 18588
13.1%
2 2
 
< 0.1%
3 3
 
< 0.1%
5 2
 
< 0.1%
5.5 2
 
< 0.1%
5.599999905 1
 
< 0.1%
5.800000191 1
 
< 0.1%
6 16
 
< 0.1%
6.400000095 2
 
< 0.1%
6.5 1
 
< 0.1%
ValueCountFrequency (%)
700 1
 
< 0.1%
500 1
 
< 0.1%
490 1
 
< 0.1%
433 1
 
< 0.1%
430 2
< 0.1%
426 2
< 0.1%
403 2
< 0.1%
394 3
< 0.1%
382.7999878 1
 
< 0.1%
380 1
 
< 0.1%

rooms
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1294761
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:22.332167image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum20
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.99433956
Coefficient of variation (CV)0.46694094
Kurtosis3.719362
Mean2.1294761
Median Absolute Deviation (MAD)1
Skewness1.0604964
Sum301027
Variance0.98871117
MonotonicityNot monotonic
2024-07-10T07:24:22.513379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 52676
37.3%
1 42029
29.7%
3 36930
26.1%
4 7091
 
5.0%
5 1802
 
1.3%
6 556
 
0.4%
7 179
 
0.1%
8 55
 
< 0.1%
10 19
 
< 0.1%
9 18
 
< 0.1%
Other values (4) 7
 
< 0.1%
ValueCountFrequency (%)
1 42029
29.7%
2 52676
37.3%
3 36930
26.1%
4 7091
 
5.0%
5 1802
 
1.3%
6 556
 
0.4%
7 179
 
0.1%
8 55
 
< 0.1%
9 18
 
< 0.1%
10 19
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
12 4
 
< 0.1%
10 19
 
< 0.1%
9 18
 
< 0.1%
8 55
 
< 0.1%
7 179
 
0.1%
6 556
 
0.4%
5 1802
1.3%

is_apartment
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size138.2 KiB
False
139990 
True
 
1372
ValueCountFrequency (%)
False 139990
99.0%
True 1372
 
1.0%
2024-07-10T07:24:22.694263image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

studio
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size138.2 KiB
False
141362 
ValueCountFrequency (%)
False 141362
100.0%
2024-07-10T07:24:22.837230image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

total_area
Real number (ℝ)

HIGH CORRELATION 

Distinct3358
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.374644
Minimum11
Maximum960.29999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:23.024595image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile32.5
Q139.299999
median53
Q372
95-th percentile127
Maximum960.29999
Range949.29999
Interquartile range (IQR)32.700001

Descriptive statistics

Standard deviation40.295864
Coefficient of variation (CV)0.64602956
Kurtosis50.131605
Mean62.374644
Median Absolute Deviation (MAD)14.200001
Skewness5.1673471
Sum8817404.4
Variance1623.7566
MonotonicityNot monotonic
2024-07-10T07:24:23.267759image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38 3580
 
2.5%
45 2807
 
2.0%
39 2463
 
1.7%
40 2188
 
1.5%
60 2108
 
1.5%
52 2078
 
1.5%
54 1992
 
1.4%
33 1935
 
1.4%
35 1818
 
1.3%
44 1492
 
1.1%
Other values (3348) 118901
84.1%
ValueCountFrequency (%)
11 2
< 0.1%
11.30000019 1
 
< 0.1%
11.5 2
< 0.1%
11.69999981 2
< 0.1%
12 3
< 0.1%
12.10000038 2
< 0.1%
12.22999954 1
 
< 0.1%
12.30000019 2
< 0.1%
12.55000019 2
< 0.1%
12.60000038 1
 
< 0.1%
ValueCountFrequency (%)
960.2999878 2
< 0.1%
925 2
< 0.1%
920 1
< 0.1%
901 1
< 0.1%
872.5999756 1
< 0.1%
800 1
< 0.1%
764.1 1
< 0.1%
761 1
< 0.1%
760 1
< 0.1%
757.7999878 2
< 0.1%

price
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct8384
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19441620
Minimum11
Maximum9.8737377 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-07-10T07:24:23.508750image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile6500000
Q18900000
median11850000
Q316950000
95-th percentile49500000
Maximum9.8737377 × 109
Range9.8737377 × 109
Interquartile range (IQR)8050000

Descriptive statistics

Standard deviation66269544
Coefficient of variation (CV)3.4086431
Kurtosis11579.848
Mean19441620
Median Absolute Deviation (MAD)3450000
Skewness88.96515
Sum2.7483063 × 1012
Variance4.3916525 × 1015
MonotonicityNot monotonic
2024-07-10T07:24:23.758291image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10500000 2287
 
1.6%
9500000 2057
 
1.5%
12500000 1982
 
1.4%
8500000 1922
 
1.4%
11500000 1855
 
1.3%
11000000 1702
 
1.2%
12000000 1687
 
1.2%
13500000 1558
 
1.1%
9000000 1493
 
1.1%
10000000 1411
 
1.0%
Other values (8374) 123408
87.3%
ValueCountFrequency (%)
11 1
 
< 0.1%
19 1
 
< 0.1%
85 1
 
< 0.1%
1500 1
 
< 0.1%
2000 3
< 0.1%
2300 1
 
< 0.1%
2400 1
 
< 0.1%
2500 3
< 0.1%
2600 1
 
< 0.1%
2700 1
 
< 0.1%
ValueCountFrequency (%)
9873737728 1
< 0.1%
9799999488 1
< 0.1%
9200000000 1
< 0.1%
8147034112 1
< 0.1%
4686425088 1
< 0.1%
4447152128 1
< 0.1%
4048056064 1
< 0.1%
3525904640 1
< 0.1%
2551801088 2
< 0.1%
2500000000 1
< 0.1%

Interactions

2024-07-10T07:24:12.920029image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:36.634681image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:39.448399image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:42.387136image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:46.305570image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:49.068685image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:51.698504image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:54.361479image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:56.872826image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:59.479302image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:02.128431image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:04.839680image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:07.668936image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:10.356177image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:13.116033image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:36.831930image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:39.650235image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:42.693432image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:46.507101image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:49.260505image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:51.893697image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:54.554466image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:57.058636image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:59.675683image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:02.333566image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:05.037384image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:07.868402image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:10.541937image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:13.303700image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:37.030250image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:39.845097image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:43.084056image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:46.706366image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:49.448152image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:52.086902image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:54.735293image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:57.243952image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:59.968544image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:02.531749image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:05.229048image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:08.065402image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:10.722545image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:13.490763image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:37.224163image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:40.038118image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:43.503457image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:46.903230image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:49.633509image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:52.277955image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:54.914467image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:57.426153image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:00.147893image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:02.729204image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:05.419948image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:08.255114image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:10.903038image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:13.800168image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:37.436713image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:40.278817image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:43.949258image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:47.109904image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:49.835641image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:52.585308image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:55.105432image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:57.620834image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:00.337446image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:02.940812image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:05.626554image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:08.478243image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:11.095689image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:13.976295image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:37.711782image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:40.468633image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:44.341563image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:47.301182image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:50.016221image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:52.759193image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:55.281346image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:57.800456image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:00.512428image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:03.131927image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:05.813313image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:08.696113image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:11.277735image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:14.143297image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:37.888618image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:40.653670image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:44.629804image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:47.483944image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:50.194935image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:52.926195image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:55.446302image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:57.970826image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:00.683031image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:03.314483image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:05.992716image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:08.873309image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:11.451366image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:14.310730image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:38.073348image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:40.836538image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:44.811925image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:47.669189image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:50.367745image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:53.096966image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:55.612583image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:58.150590image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:00.849537image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:03.494999image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:06.180348image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:09.050029image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:11.619113image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:14.481430image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:38.263788image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:41.027499image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:45.004737image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:47.862710image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:50.549227image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:53.271938image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:55.786028image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:58.330858image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:01.017817image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:03.682632image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:06.370203image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:09.231905image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:11.792842image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:14.653625image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:38.451168image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:41.217463image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:45.191884image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:48.049492image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:50.729903image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:53.446170image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:55.956105image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:58.513103image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:01.193714image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:03.864925image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:06.695672image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:09.411184image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:11.973859image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:14.842368image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:38.659672image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:41.429715image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:45.396837image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:48.259486image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:50.929701image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:53.641021image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:56.152361image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:58.720422image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:01.388336image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:04.067283image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:06.897735image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:09.610839image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:12.165725image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:15.034089image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:38.861483image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:41.637552image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:45.612766image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:48.460258image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:51.122296image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:53.830077image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:56.337903image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:58.916750image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:01.578043image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:04.263483image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:07.096050image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:09.803134image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:12.360467image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:15.219155image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:39.064521image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:41.841574image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:45.947660image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:48.683705image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:51.321753image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:54.016643image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:56.521628image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:59.112753image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:01.768113image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:04.464411image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:07.296714image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:09.992750image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:12.555514image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:15.391700image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:39.252827image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:42.035134image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:46.123143image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:48.874214image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:51.502002image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:54.189363image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:56.695937image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:23:59.296759image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:01.947641image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:04.652488image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:07.481975image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:10.174834image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-10T07:24:12.736644image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Correlations

2024-07-10T07:24:23.946828image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
build_yearbuilding_type_intceiling_heightflats_countfloorfloors_totalhas_elevatoridis_apartmentkitchen_arealatitudeliving_arealongitudepriceroomstotal_area
build_year1.000-0.0190.3610.4550.3950.7320.4910.0210.1380.435-0.201-0.006-0.2170.1860.0080.270
building_type_int-0.0191.000-0.5690.0920.0500.1060.343-0.0290.127-0.088-0.042-0.1180.117-0.369-0.189-0.295
ceiling_height0.361-0.5691.0000.0490.1280.2170.0080.0390.0000.315-0.0260.147-0.1200.4920.2190.448
flats_count0.4550.0920.0491.0000.2650.4830.085-0.0010.2360.171-0.1580.006-0.0870.001-0.0370.072
floor0.3950.0500.1280.2651.0000.5180.2700.0100.1500.240-0.0490.033-0.0860.1480.0170.146
floors_total0.7320.1060.2170.4830.5181.0000.3890.0140.3360.434-0.1050.024-0.1790.196-0.0060.221
has_elevator0.4910.3430.0080.0850.2700.3891.0000.0040.0170.219-0.0580.019-0.0380.065-0.0010.083
id0.021-0.0290.039-0.0010.0100.0140.0041.0000.0280.0220.0200.0690.0010.0440.0180.030
is_apartment0.1380.1270.0000.2360.1500.3360.0170.0281.0000.0200.032-0.025-0.0240.047-0.0120.007
kitchen_area0.435-0.0880.3150.1710.2400.4340.2190.0220.0201.000-0.1010.358-0.1340.3360.1550.395
latitude-0.201-0.042-0.026-0.158-0.049-0.105-0.0580.0200.032-0.1011.0000.034-0.0010.0630.033-0.021
living_area-0.006-0.1180.1470.0060.0330.0240.0190.069-0.0250.3580.0341.000-0.0180.4670.6530.642
longitude-0.2170.117-0.120-0.087-0.086-0.179-0.0380.001-0.024-0.134-0.001-0.0181.000-0.146-0.037-0.108
price0.186-0.3690.4920.0010.1480.1960.0650.0440.0470.3360.0630.467-0.1461.0000.6500.765
rooms0.008-0.1890.219-0.0370.017-0.006-0.0010.018-0.0120.1550.0330.653-0.0370.6501.0000.870
total_area0.270-0.2950.4480.0720.1460.2210.0830.0300.0070.395-0.0210.642-0.1080.7650.8701.000

Missing values

2024-07-10T07:24:15.649147image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-10T07:24:16.171962image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

idbuild_yearbuilding_type_intlatitudelongitudeceiling_heightflats_countfloors_totalhas_elevatorfloorkitchen_arealiving_arearoomsis_apartmentstudiototal_areaprice
011965655.71711337.7811202.648412True99.9019.9000001FalseFalse35.0999989500000.0
122001255.79484937.6080133.009710True70.0016.6000001FalseFalse43.00000013500000.0
232000455.74004037.7617422.708010True99.0032.0000002FalseFalse56.00000013500000.0
342002455.67201637.5708772.6477117True110.1043.0999983FalseFalse76.00000020000000.0
451971155.80880737.7073062.602089True33.0014.0000001FalseFalse24.0000005200000.0
562017455.72472837.7430692.7019217True90.000.0000002FalseFalse51.0099988490104.0
671964455.79558937.7226222.641805False16.1829.3400002FalseFalse44.5200009500000.0
782015255.65634537.4243353.0051211True713.500.0000001FalseFalse52.00000017990000.0
891982455.57473437.6686862.6412716True78.1819.1000001FalseFalse35.9199986300000.0
9101982455.99469837.1966862.6414212True58.0030.0000002FalseFalse50.0000005900000.0
idbuild_yearbuilding_type_intlatitudelongitudeceiling_heightflats_countfloors_totalhas_elevatorfloorkitchen_arealiving_arearoomsis_apartmentstudiototal_areaprice
1413521413531973655.59241937.6041872.4885512True17.5019.2999991FalseFalse34.9000028150000.0
1413531413542004455.85323037.6468732.7451317True97.0018.0000001FalseFalse38.0000009200000.0
1413541413551969455.62606837.6082382.502829True36.7029.0000002FalseFalse45.00000011300000.0
1413551413562008455.87264637.6342282.7412817True912.9033.9000022FalseFalse64.00000014800000.0
1413561413571971455.74040237.8345792.644289True86.0042.0000003FalseFalse64.00000010800000.0
1413571413582013455.62657937.3135032.6467225True1611.0018.0000001FalseFalse42.00000010500000.0
1413581413591960155.72747037.7686772.48805False55.2828.3300002FalseFalse41.1100017400000.0
1413591413601966455.70431537.5065842.64729True75.3020.0000001FalseFalse31.5000009700000.0
1413601413612017455.69986337.9395642.7048025True1513.8033.7000012FalseFalse65.30000311750000.0
1413611413621988455.86213337.6896132.7412817True167.6018.0000001FalseFalse38.0000008000000.0